Toyota RAV4 - RAVtivities Machine

Campaign Launch / AI-Driven Creative System (Dynamic Delivery)

For the launch of the 2017 Toyota RAV4, the campaign explored an early form of AI-driven storytelling—using machine learning to generate unique, personalized activity ideas inspired by the vehicle’s adventurous positioning.

At the center of the work was the “RAVtivities Machine,” a custom-built production system I led as Senior Producer that combined image recognition and natural language processing to generate unexpected, often playful combinations of activities tailored to different audience behaviors and interests.

Working in collaboration with Tool of North America, the AI was trained to understand a range of real-world activities and recombine them into new, dynamically generated concepts—each paired with bespoke video content designed to reflect the tone and spirit of the output.

The production was built around a modular creative system, allowing for a wide range of variations to be generated and served programmatically across digital platforms. Rather than a single narrative, the campaign functioned as a responsive framework—adapting creative in real time based on how audiences engaged with it.

To support the visual system, we developed a practical production setup that included a large-scale gimbal rig and LED environments, enabling flexible capture of content that could integrate seamlessly with dynamically generated graphics and messaging.

Content was distributed through a targeted media approach, ensuring that each viewer was served a version of the experience aligned with their behavior and interests—creating a more personalized and engaging interaction with the brand.

While developed in 2017, the campaign anticipated many of the patterns now seen in AI-assisted creative—particularly the use of generative systems to shape storytelling dynamically at scale.

Agency: Saatchi & Saatchi

Director: Steve Mapp

Production Company/AI Development: Tool of North America

Base Video (Dynamically Versioned in real time for viewer)

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